A Cartesian Workspace Generator for Robot Arm Workcell Obstacle Collision Avoidance

1991 ◽  
Author(s):  
Tak-Lai Daryl Luk ◽  
John E. Sneckenberger
Keyword(s):  
Free Space ◽  
Robot Manipulator ◽  
Joint Space ◽  
Robot Arm ◽  
New Approach ◽  
Cartesian Space ◽  
Manipulator Arm ◽  
Arm Motion ◽  
Space Boundary ◽  
Crank Mechanism

Abstract Most of the methods for planning collision-free robot manipulator arm morions to accomplish collision-free end-effector paths are based on explicit representation of the sub-space of the robot work space that is free of arm motion with obstacles collision. This sub-space is called the robot arm free space and most path planners represent this free space in joint space. If the robot arm free space is represented in joint space, then each point in the free space corresponds to a robot arm configuration for which no arm-obstacle collision occurs. This paper presents a new approach for generating the robot arm free space for an articulated type robot manipulator. This approach uses an oscillating slider crank mechanism for defining the free-space boundary when certain arm-obstacle collisions occurs. The robot arm free space, importantly, is generated in Cartesian space instead of joint space.

scholarly journals Self-tuning Fuzzy Task Space Controller for Puma 560 Robot

2018 ◽  
Vol 7 (4) ◽  
pp. 273
Author(s):  
Azita Azarfar
Keyword(s):  
High Performance ◽  
Control Method ◽  
Fuzzy Controller ◽  
Robot Manipulator ◽  
Joint Space ◽  
Robot Arm ◽  
Task Space ◽  
Scaling Factors ◽  
Cartesian Space ◽  
Self Tuning

Since in most robot applications the desired paths are determined in task space or Cartesian space, it is important to control the robot arm in task space. In this paper a fuzzy controller with modifiable scaling factors is proposed to control the robot end-effector in task space. The controller is a fuzzy system with a mechanism to change the scaling factors when the error is bounded under a predetermined value. The controller is designed in joint space and is developed to work space by using inverse Jacobian strategy. The simulations results on Puma 560 robot manipulator illustrate the high performance of presented control method.

scholarly journals Energy and Path Optimization of Robot Arm Simulator Via Multi-Objective Evolutionary Algorithm

2018 ◽  
Vol 7 (4.36) ◽  
pp. 404
Author(s):  
Z. Mohamed ◽  
N. S. Khusaini ◽  
M. A.M Anuar ◽  
R. Ramly ◽  
M. A Anuar ◽  
...  
Keyword(s):  
Minimum Distance ◽  
Minimum Energy ◽  
Path Optimization ◽  
Intelligent Robot ◽  
Robot Arm ◽  
Motion Generation ◽  
Neural Controller ◽  
New Approach ◽  
Neural Controllers ◽  
Arm Motion

The performance of robot arm motion generated via neural network are presented in this paper. The robot arm motion for obstacle avoidance simultaneously optimizing three functions; minimum distance, minimum time and minimum energy are generated. Four different initial and goal position had been chosen to test and analyze the performance of generated neural controller. The same neural controllers can be employed to a different range of initial and goal position. The motion generated yield good results in the simulator. In this research a new approach for intelligent robot arm path and motion generation are successfully implemented. 

Research on Painting Robot Manipulator for Irregular Components in Reproducing Cartridge

2011 ◽  
Vol 121-126 ◽  
pp. 1358-1362
Author(s):  
Qian Qian Chen ◽  
Xiu Ting Wei ◽  
Jiang Hai Lin ◽  
Gang Li
Keyword(s):  
Inverse Problem ◽  
Trajectory Planning ◽  
Degrees Of Freedom ◽  
Robot Manipulator ◽  
Joint Space ◽  
Forward Problem ◽  
Cartesian Space ◽  
Painting Robot

In order to implement the surface painting automation of irregular components of reproducing cartridge, a painting robot manipulator with four degrees of freedom is carried out in this paper. Kinematics forward problem and inverse problem of the manipulator are firstly formulated and then painting trajectory is described by adopting the structure of endpoints and line-style. Furthermore, painting trajectory is generated in both joint space and Cartesian space according to robot’s trajectory planning principle.

scholarly journals End effector position calculation with the ANN for tapping machine

2021 ◽  
Vol 9 (3B) ◽  
Author(s):  
Gullu Akkas ◽  
◽  
Ihsan Korkut ◽  
Murat Tolga Ozkan ◽  
◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Position Control ◽  
Robot Manipulator ◽  
High Reliability ◽  
Future Research ◽  
Robot Arm ◽  
Labor Costs ◽  
End Effector ◽  
Cartesian Space ◽  
End Point

Nowadays, manufacturers give importance to the production of machines that allow for faster production, reduce labor costs, and minimize operation errors to meet the increasing demand. The search for such machines leads the manufacturing sector to automation. In this study, an automation-supported tapping machine prototype was manufactured. Kinematic equations were used for determining the location of the end effector in Cartesian space, whereas inverse kinematic equations were used for angular positions in joint space relative to positions in Cartesian space. Based on the results of the kinematic equations, the data obtained in certain positions were taught to the system through ANN. The position values for the angles known through the artificial intelligence algorithm were taught to the system. Then, the position coordinates to be reached by this manipulator, which has four degrees of freedom, for the intermediate position coordinate values through artificial neural networks (ANN) have been obtained. It is expected that the device controlled by artificial intelligence will not be affected by the variables in parameter or force changes requiring high working performance. With the control of the positions through ANN, it has been ensured that the position control of the tapping robot manipulator is predicted based on artificial intelligence techniques depending on the angle values of the limbs, and the robot is prevented from going to a position that is on a different trajectory. Accordingly, the robot arm has been made controllable with ANN techniques. With ANN modelling, the position of the end point to perform the tapping process was estimated with high reliability. For future research, a rough simulation was made to see whether the end point would go to a different position in space.

Robust Impedance Control for Robot Manipulator

1991 ◽  
Vol 3 (6) ◽  
pp. 470-474
Author(s):  
Yoshiharu Nishida ◽  
◽  
Takashi Harada ◽  
Nobuaki Imamura ◽  
Nobuo Kimura
Keyword(s):  
Disturbance Observer ◽  
Robot Manipulator ◽  
Impedance Control ◽  
Joint Space ◽  
Experimental Results ◽  
Control Methods ◽  
Robust Controller ◽  
End Effector ◽  
Cartesian Space ◽  
Modeling Errors

In most robust impedance control methods, error factors such as disturbances and modeling errors in the joint space are dealt with. However, the dynamics for an end effector of the manipulator in the Cartesian space is more important than that of the manipulator in the joint space. In this paper, error factors are described in the Cartesian space, and the influence of these factors on the dynamics of the end-effector are considered. A robust controller is designed using either feedback of impedance error or a disturbance observer based on the Cartesian space, and its effectiveness is confirmed through experimental results.

A New Discrete Event System Model for Supervising and Controlling Robotic Arm Path Tacking Tasks Based on Adaptive Masking

2012 ◽  
Author(s):  
Soheil Arastehfar ◽  
Ying Liu ◽  
Wen Feng Lu
Keyword(s):  
Discrete Event ◽  
Joint Space ◽  
Discrete Event System ◽  
New Approach ◽  
Cartesian Space ◽  
Event System ◽  
Variable Space ◽  
Two Phases ◽  
Joint Variable ◽  
Space Description

This paper introduces a new discrete event system (DES) model for supervising and controlling trajectory planning tasks and robot motion using automata. This model is proposed based on a new approach, namely mask description. Masks are constructed adaptively and are modified based on the error between the original path and the planned path. The model acts in two phases, mask construction phase (MCP) and end-effecter positioning phase (E2P2). In MCP, it tries to plan a path, and in E2P2 it tries to place the end-effecter along the sequence of points on the path. The model describes a path in the Cartesian space and moves the end-effecter in the joint variable space, and therefore, MCP plans the path as accurate as Cartesian space description, and E2P2 position the robot as fast as joint space description. Results show that the proposed adaptive masking is remarkably efficient in computing.

Deconvolution on the Euclidean motion group and planar robotic manipulator design

Robotica ◽  
2009 ◽  
Vol 27 (6) ◽  
pp. 861-872 ◽  
Author(s):  
Peter T. Kim ◽  
Yan Liu ◽  
Zhi-Ming Luo ◽  
Yunfeng Wang
Keyword(s):  
Robot Manipulator ◽  
Practical Interest ◽  
Practical Implementation ◽  
Robot Arm ◽  
Motion Group ◽  
Euclidean Motion Group ◽  
Serial Chain ◽  
Manipulator Arm ◽  
Euclidean Motion ◽  
Manipulator Design

SUMMARYSeveral problems of practical interest in robotics can be modelled as the convolution of functions on the Euclidean motion group. These include the evaluation of reachable positions and orientations at the distal end of a robot manipulator arm. A natural inverse problem arises when one wishes to design rather than to model manipulators. Namely, by considering a serial-chain robot arm as a concatenation of segments, we examine how statistics of known segments can be used to select, or design, the remainder of the structure so as to attain the desired statistical properties of the whole structure. This is then a deconvolution density estimation problem for the Euclidean motion group. We prove several results about the convergence of these deconvolution estimators to the true underlying density under certain smoothness assumptions. A practical implementation to the design of planar robot arms is demonstrated.

Pre-Impact Configuration Designing of a Robot Manipulator for Impact Minimization

2017 ◽  
Vol 9 (3) ◽  
Author(s):  
Jingchen Hu ◽  
Tianshu Wang
Keyword(s):  
Impact Force ◽  
Robot Manipulator ◽  
Analytical Formula ◽  
Joint Space ◽  
Collision Problem ◽  
Spatial Operator ◽  
Inertia Ellipsoid ◽  
The Impact ◽  
Maximum Minimum ◽  
Simple Analytical Formula

This paper studies the collision problem of a robot manipulator and presents a method to minimize the impact force by pre-impact configuration designing. First, a general dynamic model of a robot manipulator capturing a target is established by spatial operator algebra (SOA) and a simple analytical formula of the impact force is obtained. Compared with former models proposed in literatures, this model has simpler form, wider range of applications, O(n) computation complexity, and the system Jacobian matrix can be provided as a production of the configuration matrix and the joint matrix. Second, this work utilizes the impulse ellipsoid to analyze the influence of the pre-impact configuration and the impact direction on the impact force. To illustrate the inertia message of each body in the joint space, a new concept of inertia quasi-ellipsoid (IQE) is introduced. We find that the impulse ellipsoid is constituted of the inertia ellipsoids of the robot manipulator and the target, while each inertia ellipsoid is composed of a series of inertia quasi-ellipsoids. When all inertia quasi-ellipsoids exhibit maximum (minimum) coupling, the impulse ellipsoid should be the flattest (roundest). Finally, this paper provides the analytical expression of the impulse ellipsoid, and the eigenvalues and eigenvectors are used as measurements to illustrate the size and direction of the impulse ellipsoid. With this measurement, the desired pre-impact configuration and the impact direction with minimum impact force can be easily solved. The validity and efficiency of this method are verified by a PUMA robot and a spatial robot.

ROBOTIC HANDWRITING

2005 ◽  
Vol 02 (01) ◽  
pp. 105-124 ◽  
Author(s):  
VELJKO POTKONJAK
Keyword(s):  
Mathematical Models ◽  
Muscle Fatigue ◽  
Simulation Study ◽  
Robot Control ◽  
Robot Arm ◽  
Redundancy Resolution ◽  
Kinematic Redundancy ◽  
New Concepts ◽  
Human Arm ◽  
Arm Motion

Handwriting has always been considered an important human task, and accordingly it has attracted the attention of researchers working in biomechanics, physiology, and related fields. There exist a number of studies on this area. This paper considers the human–machine analogy and relates robots with handwriting. The work is two-fold: it improves the knowledge in biomechanics of handwriting, and introduces some new concepts in robot control. The idea is to find the biomechanical principles humans apply when resolving kinematic redundancy, express the principles by means of appropriate mathematical models, and then implement them in robots. This is a step forward in the generation of human-like motion of robots. Two approaches to redundancy resolution are described: (i) "Distributed Positioning" (DP) which is based on a model to represent arm motion in the absence of fatigue, and (ii) the "Robot Fatigue" approach, where robot movements similar to the movements of a human arm under muscle fatigue are generated. Both approaches are applied to a redundant anthropomorphic robot arm performing handwriting. The simulation study includes the issues of legibility and inclination of handwriting. The results demonstrate the suitability and effectiveness of both approaches.

Sign in / Sign up

Export Citation Format

Share Document